The computer attributes for learning scale (CALS) among university students: Scale development and relationship with actual computer use for learning

Authors:
Johan van Braak;Penni Tearle
Affiliations:
Department of Education, Ghent University, Henri Dunantlaan 2, 9000 Ghent, Belgium;School of Education and Lifelong Learning, University of Exeter, UK
Venue:
Computers in Human Behavior
Year:
2007

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Abstract

The purpose of this study was twofold. First to develop an instrument, the computer attributes for learning scale (CALS) for assessing how university students perceive the attributes of computer use for learning, and secondly to examine the predictive value of the CALS in relation to the actual use students made of a computer for learning. The research was based on innovation diffusion theory, and was set in the context of higher education in Flanders, the Dutch speaking part of Belgium. The first step in the development of the computer attributes for learning scale, was to draw on the literature to determine a set of attributes which could be used in relation to the use of computers for learning. Secondly, working with a stratified sample of university students (n=237), exploratory factor analysis was used to develop a one-dimensional nine item-scale for measuring students' perceptions towards these specified attributes of a computer for learning. Next, using another similar stratified sample of the same size, confirmatory factor analysis was used to assess the stability of the one-factor structure. Finally, having developed the instrument, the predictive value of the CALS was assessed by examination of the relationship of the CALS with actual computer use for learning, when controlling for related computer variables, including computer self-efficacy, perceived usefulness of computers and computer use for personal purposes. The CALS was found to have a significant predictive value in terms of computer use for learning. In view of this it is argued that the CALS is an instrument which can be used in the future to assess the likely use students will make of a computer application in relation to their learning.